Gilles Richard
- Artificial Intelligence top 10%
- Computational Theory and Mathematics top 10%
- Molecular Biology
- Experimental and Cognitive Psychology
- Information Systems
- Co-authors
- Henri PradeDidier DuboisPeter StadlerMathieu SerrurierRobert M. KovatchMartin H. WisherAndrei DoncescuEmmanuel Roux
- Topics
- Advanced Algebra and Logic (7 papers)Logic, Reasoning, and Knowledge (6 papers)semigroups and automata theory (5 papers)
In The Last Decade
Gilles Richard
30 papers receiving 180 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 129
- Computational Theory and Mathematics 48
- Molecular Biology 25
- Experimental and Cognitive Psychology 13
- Information Systems 10
Countries citing papers authored by Gilles Richard
This map shows the geographic impact of Gilles Richard's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gilles Richard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gilles Richard more than expected).
Fields of papers citing papers by Gilles Richard
This network shows the impact of papers produced by Gilles Richard. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gilles Richard. The network helps show where Gilles Richard may publish in the future.
Co-authorship network of co-authors of Gilles Richard
This figure shows the co-authorship network connecting the top 25 collaborators of Gilles Richard. A scholar is included among the top collaborators of Gilles Richard based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gilles Richard. Gilles Richard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | Analogical proportion-based induction: from classification to creativity | 1 |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 5 | |
| 7 | 15 | |
| 8 | 5 | |
| 9 | 4 | |
| 10 | Homogenous and heterogeneous logical proportions | 1 |
| 11 | 4 | |
| 12 | Homogeneous logical proportions: their uniqueness and their role in similarity-based prediction | 7 |
| 13 | Enforcing regularity by means of analogy-related proportions − A new approach to classification | 1 |
| 14 | Analogy-Making for Solving IQ Tests: A Logical View | 3 |
| 15 | On Using SVM and Kolmogorov Complexity for Spam Filtering | 2 |
| 16 | 0 | |
| 17 | 0 | |
| 18 | 8 | |
| 19 | 26 | |
| 20 | Michael Dummett's “Frege' | 1 |
About Gilles Richard
Gilles Richard is a scholar working on Theoretical Computer Science, Computational Theory and Mathematics and Artificial Intelligence, having authored 38 papers that have together received 196 indexed citations. Recurring topics across this work include Advanced Algebra and Logic (7 papers), Logic, Reasoning, and Knowledge (6 papers) and semigroups and automata theory (5 papers). The work is most often cited by research in Artificial Intelligence (129 citations), Computational Theory and Mathematics (48 citations) and History and Philosophy of Science (8 citations). Gilles Richard has collaborated with scholars based in France, Australia and India. Frequent co-authors include Henri Prade, Henri Prade, Didier Dubois, Peter Stadler, Mathieu Serrurier, Robert M. Kovatch, Martin H. Wisher, Andrei Doncescu, Emmanuel Roux and Richard Nock. Their work appears in journals such as Fuzzy Sets and Systems, Knowledge-Based Systems and Computers & Geosciences.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.